Engine right-angle pipeline genetic algorithm planning method oriented to Manhattan space

Abstract

The invention discloses an engine right-angle pipeline genetic algorithm planning method oriented to the Manhattan space. The method comprises the following specific steps: the geometrical information of an aero-engine model is extracted through the secondary development technology in a UG model; a .txt file of the extracted information is then imported into the Matlab software, and a pipeline path is automatically calculated through the technology; a .txt file of the calculation result is finally returned to the UG model through the secondary development technology, so as to achieve visualization of an aero-engine right-angle pipeline curved-surface layout plan. The method provided by the invention has the advantages that regarding the model trend of the right-angle pipeline layout, a fixed-length individual coding method is designed to solve the pipeline layout problem; appropriate evaluation functions are established for targets such as the minimum pipeline length, the minimum number of pipeline elbows, and the minimum energy value; an engine pipe layout space obstacle model is described through a curved-surface polygon; obstacle avoidance handling adopts the approximate geodesic line intersection method. The method provided by the invention achieves the automatic and optimum engine right-angle pipeline design.

Description

technical field [0001] The invention relates to the field of optimizing the layout of right-angle pipelines on the surface of aero-engines, in particular to a genetic algorithm planning method for engine right-angle pipelines facing the Manhattan space. Background technique [0002] Complex equipment such as aero-engines usually contain a large number of pipelines that have an important impact on product performance and reliability. Space restrictions and regulatory constraints must be considered in the laying of pipelines. Manual laying will lead to repeated modifications and low efficiency. Different from traditional assembly, the difficulty of pipeline laying lies in the complexity and uncertainty of pipeline shape. A typical aero-engine usually contains about 200 pipelines. The pipelines need to be laid in a complex and constrained gyration space, and various engineering constraints must be met at the same time. The process is very complicated and time-consuming. In ord...

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Problems solved by technology

[0002] Complex equipment such as aero-engines usually contain a large number of pipelines that have an important impact on product performance and reliability. Space constraints and rule constraints need to be considered in the laying of pipelines. Manual laying will lead to repeated modifications and inefficiency

Different from traditional assembly, the difficulty of pipeline laying lies in the complexity and uncertainty of pipeline shape

A typical aero engine usually contains about 200 pipelines, which need to be laid in a complex and constrained slewing space, and also need to meet various engineering constraints, the process is very complicated and time-consuming

In order to realize the automatic laying of pipelines, many scholars have conducted research on pipeline layout issues and achieved certain results. However, due to the complexity of pipeline layout constraints, a set of mature theories and methods have not yet been formed.

[0003] The determination of the pipeline layout is a very complicated process. In the field of external pipeline laying at home and abroad, manual laying and adjustment are still the main method. The laying is random, the modification is not easy, the laying period is long, and the cost is high, which restricts the progress of the entire project.

Especially in recent years, with the continuous maturity of computer technology, research on the use of computers to assist the laying of pipelines has begun at home and abroad. Opening obstacles still requires manual intervention to complete, which still restricts the development of pipeline layout design to a certain extent

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